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What steps are you taking to move the #AIGovernance conversation beyond ethics to include the more challenging topic of deep model assurance?

www.linkedin.com/feed/update/...

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The core issue is #governance. When we deploy #AI systems that are unpredictable by design, we move from managing data risk to managing systemic operational uncertainty. This requires a different, more robust approach to assurance than simply monitoring for output bias. #TechStrategy

🧵 4/4:
I explore this in my latest article to consider why your data product must become an MCP Server and what that means for your skills and strategy.

www.linkedin.com/pulse/you-bu...

#ModelContextProtocol #DigitalTransformation #AI

🧵 3/4:
The Model Context Protocol (#MCP) is key to making your data products—currently dashboards, models, and more—discoverable and usable by AI orchestration engines. Without it, your information architecture risks becoming rapidly obsolete.

🧵 2/4:
While we're diligently building robust data platforms and dashboards, a seismic shift is underway: enterprise users increasingly demand direct answers, not just static displays, powered by #ConversationalAI.

This means adopting an #AIFirst paradigm for your entire #DataArchitecture.

🧵3/3 But they are making it harder to love them. In any case, a multi-cloud strategy has long been the recommended architecture, despite the obvious overheads and drawbacks. Scandalous that several banks are down.

Good luck to all the ops teams.

🧵2/ brought everything down in (from memory) 2023.

I have been an AWS user for longer than anyone else who is still using it. Huge advocate. I even used to host the Frequently Asked Questions for it, back in the day when AWS was just the advertising API.
web.archive.org/web/20070127...

Tools have always shaped how we think. Socrates worried about children reading too much, not being able to remember things anymore and not learning the right (Socratic) way because they couldn't have a dialogue.

3/3
👉 Ask not if the #AI is perfect, ask if it is an improvement on what we do now and if you can control the errors, omissions, and mistakes that are inevitable in any decision process, whether made by human or algorithm. 👈

2/3
Our monkey brains are rubbish at any sort of complex rational thought. And yet we manage to make do and make progress.

Are there any of my readers who have not regretted a decision they made in error at the time because of bias of failure to think it through?
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2/2
The data scientist standing beside him whispers, “...Now ask it to show you the most valuable customers you're about to lose...”

The senior data scientist adds, “...and what you can do to retain them.”

#PowerBI #Copilot #JustSaying

www.linkedin.com/feed/update/...

Kids: it isn't "Big Data" unless you *have* to throw >99.9% of it away.

Matt Strassler has a good overview here: profmattstrassler.com/2024/10/21/i...
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